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Detecting offensive messages using Deep Learning: A micro-service based app...

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Hult International Business School

1355 Sansome Street

San Francisco, CA 94111

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Speakers: Ali Khatri & Alexander O'Connor
Talk Title: "Detecting offensive messages using Deep Learning: A micro-service based approach." (50-min Technical Talk)

Ali's Bio:
https://www.linkedin.com/in/alizishaan-khatri-32a20637/
Ali's passions revolve around two things: using technology to solve real-world problems and sharing solutions with the community. He is currently a Machine Learning Engineer at Pivotus Ventures, a startup focussed on humanizing the banking experience. Outside of work, Alizishaan likes to balance his time between mountaineering, skiing, traveling & photography.

Alexander's Bio:
LinkedIn: https://www.linkedin.com/in/oconnoat/
Alexander O'Connor is Director of Research with Pivotus, a banking startup bringing human contact back to banking. At Pivotus, Alex is responsible for data wrangling and machine learning. Previously, he worked as a researcher and academic in universities in Dublin Ireland (DCU & Trinity College), where he worked on personalization and natural language processing.

Talk Abstract:
What are you doing to control abusive content on your platform? Can your current solution tell the difference between “f**king awesome” and “f**king loser”? Can it detect racist and sexist content?

You will learn how to build a deep learning based solution and deploy it as a micro-service.

This talk focuses on :
- The shortcomings / common pitfalls of current approaches in terms of:
- Functionality
- Scalability
- Handling the ambiguities in defining offensive content
- Using a Deep Learning based approach to detect offensive content
- Productionizing the solution

Don't forget to register for ODSC East Conference: https://odsc.com/boston

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Hult International Business School

1355 Sansome Street

San Francisco, CA 94111

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